[PDF] Top 20 Document Level Machine Translation with Word Vector Models
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Document Level Machine Translation with Word Vector Models
... monolingual vector models as semantic space language models (Docent + monoSSM) and the bilingual ones (Do- cent + ...our word embeddings in the translation process and are consistent ... See full document
8
Word Level Confidence Estimation for Machine Translation
... language translation corpus containing the verbatim transcriptions of the speeches in the European Parliament Plenary Sessions ...The translation direction is from Spanish into ...probability models ... See full document
32
Word Representation Models for Morphologically Rich Languages in Neural Machine Translation
... for Machine Translation. Re- cently various character-level composi- tional models were proposed to address this ...soft-attentional models of trans- lation for character-level ... See full document
6
Document Level Adaptation for Neural Machine Translation
... the machine translation out- put the same ...novel word, we score its aligned machine translated to- ken as correct if it matches the aligned reference ... See full document
10
Vector Space Models for Phrase based Machine Translation
... Arabic word f , and the similarity is computed between the projec- tion and the representation of the English word ...the word representations are encoding some information about the words, although ... See full document
10
A Document Level SMT System with Integrated Pronoun Prediction
... didates are represented by the TL words aligned to the syntactic head of the source language mark- able noun phrase as identified by the Collins head finder (Collins, 1999), again represented as one- hot vectors. These ... See full document
6
Extending Machine Translation Evaluation Metrics with Lexical Cohesion to Document Level
... and document-level met- ...and document-level metrics, for instance, ...is word choice oriented, which is only sensitive to the reiteration and semantic relat- edness of words in MT ... See full document
9
On the Importance of Word Boundaries in Character level Neural Machine Translation
... the machine translation task from English into five languages from different language families and exhibiting distinct mor- phological typology: Arabic (templatic), Czech (mostly fu- sional, partially ... See full document
7
Lexical Chain Based Cohesion Models for Document Level Statistical Machine Translation
... in Document-Level SMT In discourse analysis, cohesion is often studied to- gether with coherence which is another dimension of the linguistic structure of a text (Barzilay and Elhadad, ...various ... See full document
11
Novel Document Level Features for Statistical Machine Translation
... of word align- ments, maximum entropy, GIZA++ and HMM alignment, are used to generate phrase pairs as the prior model in ...and document level MaxEnt ...ment level features, LM, and other ... See full document
5
Cache based Document level Statistical Machine Translation
... Statistical machine translation systems are usually trained on a large amount of bilingual sentence pairs and translate one sentence at a time, ignoring document-level ...to ... See full document
11
Incorporating Word Reordering Knowledge into Attention based Neural Machine Translation
... age vector for keeping the attention history to acquire accurate ...distortion models explicitly capture word reordering knowledge through estimating the probability distribu- tion of relative jump ... See full document
11
Metrics for Evaluation of Word level Machine Translation Quality Estimation
... of machine translation (MT) is a task of determining the quality of an au- tomatically translated text without any oracle (ref- erence) ...a word or a phrase (Gan- drabur and Foster, 2003)) it ... See full document
6
Word Level Confidence Estimation for Machine Translation using Phrase Based Translation Models
... opment set beforehand. The performance of the con- fidence measure is evaluated using the Classification Error Rate (CER). This is defined as the number of incorrect tags divided by the total number of gener- ated words ... See full document
8
Lexical Chains meet Word Embeddings in Document level Statistical Machine Translation
... the translation of a phrase with another from the phrase table), swap-phrases (ex- changes phrases), move-phrases (randomly moves phrases in the sentence), and resegment (changes the segmentation of the source ... See full document
11
Combining Word Level and Character Level Models for Machine Translation Between Closely Related Languages
... Transliteration. The top rows of Table 3 show the results for Macedonian-Bulgarian transliteration. First, we can see that the BLEU score for the original Macedonian testset evaluated against the Bulgarian reference is ... See full document
5
Incorporating Word and Subword Units in Unsupervised Machine Translation Using Language Model Rescoring
... We employ subword units (Sennrich et al., 2016a) to tackle the morphological richness prob- lem. There are two advantages of using the subword-level. First, we can alleviate the OOV is- sue by zeroing out the ... See full document
8
Document Level Machine Translation Evaluation with Gist Consistency and Text Cohesion
... evaluating translation quality for one document should be to what degree the MT output correctly communicates the main idea of origin ...each document can be characterized by a particular set of ... See full document
8
Greedy Search with Probabilistic N gram Matching for Neural Machine Translation
... Neural machine translation (NMT) models are usually trained with the word-level loss using the teacher forcing algorithm, which not only evaluates the translation improperly but ... See full document
7
Vector of Locally Aggregated Word Embeddings (VLAWE): A Novel Document level Representation
... We plug the VLAWE representation, which is learned in an unsupervised manner, into a classi- fier, namely Support Vector Machines (SVM), and show that it is useful for a diverse set of text clas- sification tasks. ... See full document
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